AlKadhum Journal of Science
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Development of an Optical Crystal Fiber Sensor for Early Detection of Tuberculosis
No full textTo this day, tuberculosis remains one of the most severe threats to public health on a global scale, which is why there is a pressing need for the development of diagnostic techniques that combine high levels of precision, speed in producing findings, mobility, and risk reduction. This work\u27s planned scope is constructing a photonic crystal fiber sensor with a susceptible non-complex core intended to detect tuberculosis at wavelengths ranging from 1 µm to 2.2 µm. This study introduces an innovative biomedical photonic crystal fiber sensor capable of accurately detecting tuberculosis bacteria across all four strains and effectively distinguishing between them. To carry out numerical studies, the proposed structure uses a technique known the full-vector finite element method (FV-FEM). Compared to earlier biomedical sensors based on photonic crystal fiber, the sensor that has been developed demonstrates an exceptionally high relative sensitivity in detecting various kinds while also displaying a deficient level of loss. The proposed sensor has an effective size of 38 µm2, a sensitivity of 99.9%, and a low confinement loss of 10-11 dB/m. To validate the usefulness of the proposed layout and establish its integrity, a detailed analysis is performed by contrasting the results of this study with the most current research published on photonic crystal fiber.
Integrated Approach for Evaporation Assessment in Al-Wand River Basin
No full textEstimating evaporation is crucial for planning and developing water resource development. The study discusses fuzzy logic’s ability to model monthly pan evaporation by MATLAB for Khanaqin Meteorological Station to the period (1981-2000). The model includes monthly maximum and minimum temperatures, wind speed, and relative humidity data gathered from stations situated in Al-Wand River Basin were used as input components in the model. The fuzzy logic results were evaluated with monthly average evaporation from Khanaqin Station using the coefficient of determination (R2). The results showed a converged value between the value of evaporation between Khanaqin Station and fuzzy logic, the coefficient of determination (R2) reached to 92% with the accepted trend in monthly evaporation for twenty year
Calculation of the Electronic Properties Phthalocyanine (H2Pc), Silicon Phthalocyanine (Sipc), Phosphorus Phthalocyanine (PPc) and Energy Gap by the AM1 Method
No full textMany semi-empirical methods are available in Gaussian 16. This patch enables analytical gradients and frequencies in addition to increasing efficiency by replacing the code from MOPAC open source, AM1 and PM3 technologies. In the case of a pure molecule, the values of total energy, bond energy, electronic energy, and nuclear energy (-170.893, -1496.855, -4332.708, 45) Kcal/mol have been successively added. After adding Si and P to the free Phthalocyanine molecule, the values transformed to (-133.30, -4987.486, -1294.027, 11.607) Kcal/mol. For the two resulting molecules (PcSi and PcP), the values became (-136.108, -4858.63, -9354.14, 79.930) Kcal/mol. Notably, the first number indicated an increase. Specifically, for total energy numbers, there was a decrease from -170.893 to -133.3 Kcal/mol when adding Si, and a decrease to -136.108 Kcal/mol when adding P. Overall, the energy value increased with both additions, but the bonding energy notably decreased with Si (-1496.855 to -4987.486 Kcal/mol) and P (-4858.63 Kcal/mol). Electronic energy increased from -4332.708 to -1294.027 Kcal/mol when Si was added. Nuclear energy decreased from 45.036 to 11.607 Kcal/mol when Si was added (increasing to 79.930 Kcal/mol with P). The Heat of Formation (H.o.F.) in Kcal/mol equaled 1565.04 when P was added, 1193.384 when Si was added, and 1531.528 when P was added again. The substantial impact of silicon on Phthalocyanine was evident. Furthermore, the dipole moment of the Phthalocyanine molecule, initially at D 3.687, decreased to D 2.093 and D 4.137 when Si was added first and P the second time, showcasing the significant impact of P due to its high atomic number. Determining the HOMO and LUMO and computing the values of Wavenumber, Wavelength, and Symmetry for the three molecules provided a clear illustration. The computation of electrical potential, electronic orbitals, and energy gap revealed an electronic density of 0.346 eV in the case of the free molecule H2Pc, 5.006 eV in the molecule PPc, and 5.660 eV in the case of SiPc. This offers a comprehensive understanding of the impact of adding P and Si to H2Pc
ADOPTION OF CLOUD COMPUTING AS A BUSINESS SOLUTION FOR SME’s
No full textCloud Computing has evolved over the years in providing platforms for SME\u27s to thrive while accessing technology on a different level and capacity. More businesses are moving into the cloud based on criteria such as insights on big data, sustainability, flexibility and scalability, efficient collaboration, business continuity, disaster recovery, and cost-effectiveness. The structure and logistics behind how the cloud works have been explained in detail. Cloud deployment models include public, private, community, and hybrid cloud. Typical cloud services include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Cloud characteristics and features cut across different criteria which eventually combine to form the benefits and challenges. The focus of this paper is on evaluating why cloud computing has become one of the best solutions for SME\u27s worldwide and the need for businesses to begin to consider moving to the cloud. The pandemic has also proven the essence of cloud computing as a business solution for SME\u27s
A Statistical Analysis of COVID-19 Image Detection Using the Wavelet Transform
No full textCoronavirus (COVID-19), a newly discovered virus that shows similar symptoms to pneumonia, has been sweeping the world since December 2019. The World Health Organization (WHO) declared this disease a global pandemic because of its high contagiousness. This virus can cause fatal symptoms in some patients. Therefore, early detection of COVID-19 is crucial. The main challenge in detecting COVID-19 is that it affects the human body\u27s respiratory systemTop of Form. In this work, wavelet transduction is used to integrate multifocal images in order to detect COVID-19. In order to detect COVID-19, MRI and CT were used. Clinical diagnoses were supported by the multifocal image. Seven wave-based algorithms were used: bior2.2, coif2, db2, dmey, rbio2.2, sym4, and haar. This method successfully integrates data acquired from CT and MRI scans, resulting in a merged image that enhances the efficiency of disease diagnosis. MATLAB is employed for evaluating the algorithm\u27s effectiveness, with the entropy, PSNR and factor serving as metrics to assess the efficiency of image fusion. In a statistical analysis, the images demonstrated superior attributes over CT and MRI images.
Artificial Neural Network-Powered, Driverless Vehicle Concept Development
No full textAutonomous cars are now possible due to significant advances in robotics and intelligent control systems. Before these vehicles can safely operate in traffic and other hostile environments, there are many navigation, vision, and control issues. We want techniques that are both cost-effective and efficient, so that the field of research and academia may fully embrace self-driving cars. Within this scenario, we need something that can convert people to autonomous automobiles and include existing vehicles so that academics and explorers can access them. This study proposes a flexible mechanical layout that can be assembled in a short time and installed in most modern automobiles; it can also be used as a stepping stone in the development of autonomous vehicles. Using various actuators, conventional automobiles can be converted into autonomous vehicles. In the context of motor vehicle automation, motors are often used as actuators. In addition to motors, a pneumatic system was developed to automate the predetermined steps. An autonomous vehicle\u27s mechanical arrangement is crucial, and it must be regularly updated and built to be robust in the face of dynamic conditions. We re-implemented two additional convolutional neural networks in an effort to conduct an objective test of their proposed network and compare our system\u27s structure, technical complexity, and performance test during autonomous driving with theirs. This predicted network is around 250 times larger than the Alex Net network and four times larger than Pilot Net after training. Although the complexity and measurement of the publication\u27s system are lower than other models that contribute lower latency and greater speed throughout inference, the operation was claimed by our system, which achieved autonomous driving with an equivalent efficacy as that achieved with two other models. The projected deep neural system reduces the need to infer ultra-fast computational hardware. This is important for cost efficiency, scale, and cost
Design and Implementation of a Secured Communication System Using Chau’s Circuit
No full textThe Chua circuit is one of the most basic nonlinear circuits that exhibits the most complicated dynamical behavior, including chaos, which exhibits a variety of bifurcation occurrences and attractors.Proteus software was used to develop and simulate the Chua masking communication circuits in this paper. The transmitter and receiver sections of the electronic circuit oscilloscope outputs of the realized Chua system are also shown. The accuracy of the intended and implemented Chua chaotic oscillator circuits is demonstrated using simulation and oscilloscope outputs. The Chua system is designed for chaotic communication circuits with masking. The acquired data is utilized to demonstrate the Chua chaotic system\u27s usefulness in secure communication applications .The results were compared with previous studies on circuit implementation and experimental results that indicate the double-pass attractor, in addition to the advantages of this technique over others in the fields of communication, image coding, and simulation of neural systems
An Explainable Content-Based Course Recommender Using Job Skills
No full textThe large number of courses offered in universities and online studies made it difficult for students to choose the courses that suit their interests and career goals, which led students to lose many opportunities to be employed in the job they wanted. To keep pace with the rapid development of technology, and instead of relying on the job title as was previously done, the employers began to identify the skills required for a job. The competencies of the candidates are then examined and evaluated according to those requirements. Thus, it has become necessary for students to take courses that suit their future professional interests, ensuring that they are employed in the job they desire and supporting their long-term career success. Fortunately, the emergence of skills-based employment has provided an opportunity for universities and colleges to create a clearer path to the courses offered to allow students to take courses that match their future career interests. In this study, we used K-Mean clustering algorithm, TF-idf approach, and content-based filtering algorithm to provide relevant courses for students based on the required job with an explanation of why these courses are recommended. Our result illustrates that our method offers many advantages compared with other recommender systems. our system converts a simple course recommendation into a tool for discovering skills. Since many recommendation systems work as black boxes, we designed our system to recommend the relevant course with explaining why these courses are recommended, which will add a factor of transparency to our system and confirms the reliability of the system to the students
High-quality data transmitted by ROF, FSO and DPSK systems
No full textIn communications, many Factors affect the quality and quantity through different of radio transmission via optical transmission in open space. In this study OPTI System software is utilized to simulate a real-world configuration of free space optical (FSO), and differential phase shift keying (DPSK) techniques. The ROF signal was transmitted over FSO by loading the ROF signals via light as a carrier signal. With regards to the bit error rate (BER), visual, and receiving energy style scheme, channels FSO one and two are contrasted and examined. The results showed that data was successfully received over long distances of up to 100 km with a Q factor of 23.224. Future installations of several FSO system processes will be possible to accommodate the growing demand for high-bandwidth communications
Opinion Mining in Arabic Extremism Texts: A Systematic Literature Review
No full textIn this paper, a systematic literature review was provided that investigated the present evidence regarding extremist words in Arabic opinion mining methods. This study aimed to perform a Systematic Literature Review (SLR) in order to detect, evaluate, and synthesize the existing evidence regarding opinion mining techniques for extremist Arabic text. From the SLR, it is evident that opinion-mining techniques have several opportunities for detecting extremism in the Arabic text. Over the past few years, multimedia sentiment analysis has gained traction as visual content is becoming more incorporated into social media networking. Opinion mining is the process of identifying, extracting, and categorizing views about anything. It is a sort of Natural Language Processing (NLP) used to track public sentiment about a certain law, policy, or marketing, for example. It entails the creation of a method for collecting and analyzing comments and opinions concerning legislation, regulations, policies, and so on that are posted on social media. The process of information extraction is critical since it is both a beneficial tool and a difficult undertaking. In this article, we have examined the recent and advanced methodologies to extract sentiment from a web-wide item, opinion-mining methods must be automated. Also, we have analyzed the novel Artificial Intelligence and lexical-based algorithms for sentiment analysis. These methodologies find better applications in the customer feedback analysis of any organization